r"""Test whether the given object or class is persistent, i.e., whether it will save its source code when pickled.

r"""Returns the names of all statistics broadcasted so far that match the regular expression specified at construction time.

Fast CUDA implementation of `bias_act()` using custom ops.

Slow reference implementation of `bias_act()` using standard TensorFlow ops.

r"""Check that the given object is pickleable, raising an exception if it is not. This function is expected to be considerably more efficient

Slow and memory-inefficient reference implementation of `filtered_lrelu()` using existing `upfirdn2n()` and `bias_act()` ops.

r"""Query the source code of a given Python module.

r"""Get or create a Python module for the given source code.

r"""Synchronize the global cumulative counters across devices and processes. Called internally by `Collector.update()`.

Slow reference implementation of `upfirdn2d()` using standard PyTorch ops.

r"""Returns the averages accumulated between the last two calls to `update()` as an `dnnlib.EasyDict`. The contents are as follows:

Calculate quality metrics for previous training run or pretrained network pickle. Examples: \b # Previous training run: look up options

Finds the python object with the given name and calls it as a function.

Convert an image dataset into a dataset archive usable with StyleGAN2 ADA PyTorch. The input dataset format is guessed from the --source argument

Convert legacy network pickle into the native PyTorch format. The tool is able to load the main network configurations exported using the TensorF

Render a latent vector interpolation video. Examples: \b # Render a 4x2 grid of interpolations for seeds 0 through 31. python gen_vi

Generate images using pretrained network pickle. Examples: \b # Generate an image using pre-trained AFHQv2 model ("Ours" in Figure 1, le

Finds the python object with the given name.

Determine whether the given object is a top-level function, i.e., defined at module scope using 'def'.

Determine whether the given object is a valid URL string.

Train a GAN using the techniques described in the paper "Alias-Free Generative Adversarial Networks". Examples: \b # Train StyleGAN3

Interactive model visualizer. Optional PATH argument can be used specify which .pkl file to load.

Compare average power spectra between real and generated images, or between multiple generators. Example: \b # Calculate dataset mea